Responsibilities
- Assist in developing components of AI agent frameworks, including orchestration workflows, tool integrations, and basic state management.
- Build and maintain backend services in Python (or Java/Go/C++) to support AI inference and data processing.
- Support development of LLM-based applications, including prompt design, tool usage, and evaluation workflows.
- Contribute to model integration and deployment, including working with APIs and inference endpoints.
- Help develop microservices and data pipelines for processing time-series and streaming data.
- Assist in integrating AI services with grid systems such as SCADA and simulation tools.
- Participate in performance tuning and debugging of distributed systems under guidance.
- Contribute to CI/CD pipelines, testing, and monitoring for AI services.
- Implement logging and basic explainability features for AI outputs.
- Collaborate in code reviews and contribute to shared codebases following engineering best practices.
Basic qualifications
- Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field.
- 0–3 years of software development or AI/ML experience (internships/projects included).
Preferred qualifications
- Proficiency in Python; exposure to Java, C++, or Go is a plus.
- Basic understanding of machine learning concepts and LLM applications.
- Familiarity with APIs, backend development, and microservices concepts.
- Exposure to cloud, containers (Docker), or orchestration (Kubernetes) is a plus.
- Understanding of data structures, algorithms, and software engineering fundamentals.
- Interest in distributed systems and real-time data processing.
- Familiarity with power systems (EMS, DMS, SCADA) is a plus but not required.
- Hands-on experience building production AI systems in a mission-critical domain.
- Mentorship from experienced engineers in AI, distributed systems, and grid software.
- Exposure to real-world applications of AI in energy and infrastructure.
- Opportunities to grow into more advanced engineering roles.
Tags & focus areas
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